| Commit message (Collapse) | Author | Age | Files | Lines |
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Code documentation of numpy scalar types indicated the wrong type
(number) for the kind 'i'. This edit moves the indication to the
right type (unsignedinteger).
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BUG: Remove invalid read in searchsorted if needle is empty
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The tests are a bit ugly, but the cache otherwise hides the errors
away during testing.
The ternary operation did not work, because complex types do not like
assignment of 0.
Closes gh-11261
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BUG: Work around past and present PEP3118 issues in ctypes
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np.dtype(type(ctype_obj))
Fixes gh-10528
Fixes gh-10978
Fixes gh-11150
A warning is thrown when ctypes misbehaves, in order to not hide issues that need fixing upstream
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* update docstring of interp()
* change "calculate" to "evaluate" to be consistent
* remove "values"
* make "data points" consistent
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BUG: Prevent stackoverflow in conversion to datetime types
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Fixes gh-11154
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BUG: Set ndarray.base before __array_finalize__
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Fixes #11237
Without this, we expose arrays to python before the lifetime of their buffer has been correctly attached, which can lead to use-after-frees (see the referenced issue).
Unfortunately, this means that `PyArray_SetBaseObject(arr, base)` is still broken in downstream code for any cases where `arr.__array_finalize__ is not None`. We may have no choice but to deprecate this function, and expose PyArray_FromDescrAndBase. But lets leave fixing public API to a later date...
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Also move an assignment ouf of an if.
Only targeting calls that then go on to call PyArray_SetBaseObject
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TST: Do not use empty arrays in tests (unless they are not read)
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Not initializing arrays throws off valgrind, so avoid it here. For a while
I thought it was just a false positive due to some SSE string compare function.
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WIP: Remove fragile use of __array_interface__ in ctypeslib.as_array
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Everything behaves a lot better if we let the array constructor handle it, which will use the ctypes PEP3118 support.
Bugs this fixes:
* Stale state being attached to pointer objects (fixes gh-2671, closes gh-6214)
* Weird failure modes on structured arrays (fixes-10978)
* A regression in gh-10882 (fixes gh-10968)
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ENH: Implement axis for generalized ufuncs.
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Much faster, and much less code duplication than I feared.
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It is only allowed for gufuncs with a single, shared
core dimension.
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BUG,MAINT: Ensure masked elements can be tested against nan and inf.
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This brought to light two bugs in tests, which are fixed here, viz.,
that a sample ndarray subclass that tested propagation of an added
parameter was incomplete, in that in propagating the parameter in
__array_wrap__ it assumed it was there on self, but that assumption
could be broken when a view of self was taken (as is done by
x[~flagged] in the test routine), since there was no
__array_finalize__ defined.
The other subclass bug counted, incorrectly, on only needing to provide
one type of comparison, the __lt__ being explicitly tested. But flags
are compared with __eq__ and those flags will have the same subclass.
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The removal of nan and inf from arrays that are compared using
test routines like assert_array_equal treated the two arrays
separately, which for masked arrays meant that some elements would
not be removed when they should have been. This PR corrects this.
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MAINT: Implement float128 dragon4 for IBM double-double (ppc64)
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Replace `NPY_UNUSED(*param)` by `*NPY_UNUSED(param)`.
Closes #11267.
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BUG: ensure extobj and axes have their own references.
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MAINT: Cleanup dragon4 code in various ways
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[ci skip]
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Define the float format macros NPY_*_BINFMT.
Reorg formatting functions to refer to specific formats.
Make BigInt variables static to avoid using up stack space.
Dragon4 now takes a BigInt mantissa, not uint64.
Define Dragon4_Options struct to pass options.
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BUG: Remove errant flag meddling in .real and .imag
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Fixes #11245
PyArray_NewFromDescr sets the flags just fine by itself.
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MAINT/BUG: Remove out-of-band reference count in PyArray_Newshape, fix memory leak
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`PyArray_UpdateFlags(view, NPY_ARRAY_UPDATE_ALL);` is already called within PyArray_NewFromDescr_int
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MAINT: Use PyArray_NewFromDescr where possible, remove unused definitions
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This makes it a little easier to convert these calls to PyArray_NewFromDescr_int if new parameters are needed in future.
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